Ester Gutiérrez

Slacks-based measure of efficiency of airports with airplanes delays as undesirable outputs

This paper reports the slacks-based measure (SBM) of efficiency of 39 Spanish airports for years 2006 and 2007. In addition to the conventional outputs (namely aircraft traffic movements, passenger movements and cargo handled), two undesirable outputs have been considered: percentage of delayed flights and average conditional delay of delayed flights. The inputs considered quantify the physical infrastructure of the airports and are considered non-discretionary. The proposed Data Envelopment Analysis (DEA) approach assumes variable returns to scale and joint weak disposability of the desirable and undesirable outputs. The SBM model used has been found to have more discriminatory power than the common directional distance function approach. Also, the inclusion in the analysis of the undesirable effects of airport operations leads to more valid results. The results show that in both years more than half of the airports are technical efficient with the rest showing in general large inefficiencies due to slacks in the different outputs, slacks that the proposed SBM approach is able to identify and quantify. Overall, the system has significant improvement potential in cargo and to a less extent in passengers and percentage of delayed flights.

Data envelopment analysis of mutual funds based on second-order stochastic dominance

Although data envelopment analysis (DEA) has been extensively used to assess the performance of mutual funds (MF), most of the approaches overestimate the risk associated to the endogenous benchmark portfolio. This is because in the conventional DEA technology the risk of the target portfolio is computed as a linear combination of the risk of the assessed MF. This neglects the important effects of portfolio diversification. Other approaches based on mean-variance or mean-variance-skewness are non-linear. We propose to combine DEA with stochastic dominance criteria. Thus, in this paper, six distinct DEA-like linear programming (LP) models are proposed for computing relative efficiency scores consistent (in the sense of necessity) with second-order stochastic dominance (SSD). The aim is that, being SSD efficient, the obtained target portfolio should be an optimal benchmark for any rational risk-averse investor. The proposed models are compared with several related approaches from the literature.

A slacks-based network DEA efficiency analysis of European airlines

Conventional data envelopment analysis (DEA) models consider a system as a single-process ‘black box’. There are, however, DEA approaches that consider a system as composed of distinct processes or stages, each one with its own inputs and outputs and with intermediate flows among the stages. In this paper, a network DEA approach to airline efficiency assessment is presented. One conclusion of the study is that the network DEA approach has more discriminative power than the single-process DEA approach and that the computed targets, efficiency scores and rankings are more valid. This is because network DEA allows for a more fine-grained analysis that leads to a more realistic estimation of the overall system production possibility set than the one assumed by conventional DEA. In other words, compared with network DEA the conventional, single-process DEA represents an aggregated analysis that merges all system processes with their inputs and outputs and ignores their internal flows. The main drawbacks are the need for more detailed data (i.e. at the process level) and the greater complexity of the resulting models, especially if there are inputs or outputs that are shared among the processes.

TSD-consistent performance assessment of mutual funds

This paper presents three new data envelopment analysis-based approaches to assess the relative efficiency of mutual funds (MFs). Each model considers an appropriate risk measure as input and an appropriate return measure as output. The risk and return measures have been chosen so that the proposed models are consistent with third-order stochastic dominance (TSD) rules. This means that the MFs found efficient by the proposed models are also, in a necessity condition sense, TSD efficient and therefore of highest consideration for all non-satiated, risk averse investors that also have decreasing absolute risk aversion. The proposed approach is illustrated with real data on a set of Spanish MFs and compared with existing approaches from the literature based on Mean–Variance and Mean–Variance–Skewness models.

Fuzzy Grey Cognitive Maps in reliability engineering

Current industrial equipment has become more complex and huge. In this case, the conventional reliability techniques cannot correctly support functional assessment. This paper integrates an innovative soft computing methodology, Fuzzy Grey Cognitive Map (FGCM), into a traditional reliability analysis for better knowledge. FGCMs are used for evaluating, modelling and aiding decision-making by examining causal relations among relevant domain concepts. The proposed procedure is illustrated with a reliability analysis of a transformer active part. Twenty failure causes in the transformers active part are identified and assessed. In addition, six failure scenarios are simulated. The results revealed the potential of the combination of FGCM and failure analysis for complex systems. The proposed methodology exposes the potential benefits it could provide in order to assist electric power system decision-makers to supply its customer electrical energy with a high degree of reliability.

Data envelopment analysis of the human development index

The human development index (HDI) measures progress in human development along three dimensions: longevity, knowledge and standard of living. Each dimension is measured by an index and a simple average computed. A total of four indicators are used: life expectancy at birth, adult literacy rate, gross enrolment ratio and gross domestic product (GDP) per capita. In this paper, data envelopment analysis (DEA) is used to combine these four indicators. DEA allows each country to determine the weights of these components thus removing any argument about unfair weights. Consistent with the HDI, the proposed DEA model computes a range-adjusted measure (RAM) of efficiency. Results for the data of years 2000 through 2004 are presented. DEA efficiency scores are shown to be highly correlated with HDI. A sensitivity analysis of DEA efficiency scores w.r.t. the variables has also been performed, showing that the kernel of the index are the literacy and GDP components.

A competing risks approach for time estimation of household WEEE disposal.

The recent growth in the number of electrical and electronic devices is viewed as one the priority waste streams in European Union waste management policy. This paper presents the findings of a survey to study domestic habits with respect to Waste Electrical and Electronic Equipment (WEEE) in Spain. A specific problem when performing this estimation arises from the fact that consumers quite often store old appliances at home when they are no longer used. Focusing on four different types of appliance, survival analysis (SA) is used to study both the usage span and the reasons for no longer using each device. The time that the discarded products were kept at home before being disposed of was studied using competing risks (CR) analysis. The results of the analysis provide information on the distribution of the studied variables for the different outcomes as well as the influence exerted by the socio-demographic variables considered. Relations between these characteristics and the storage time of the appliances before disposal emerge based on survey data. For instance, the CR model finds that the storage time of the some appliances (i.e. refrigerator) is related to these social-demographics factors. However, other appliances (i.e. microwave oven) are less influenced by these factors. The attitude and motivation of the respondents to the survey as regards the End-of-Life of appliances were also analysed. A majority of respondents do not store discarded appliances at home. The first reason for storing appliances at home is the possibility of it being useful in the future and the second that the respondents did not know what to do with them.

Assessing relationships among life-cycle environmental impacts with dimension reduction techniques

Nowadays, there is a trend in many countries towards more environmentally benign products and processes. Life-Cycle Assessment (LCA) is a quantitative analysis tool developed and utilized for the evaluation of environmental impacts occurring throughout the entire life-cycle of a product, process or activity. LCA requires a large amount of data in its different phases and can also generate large amounts of results which may be hard to interpret. In order to uncover and visualize the structure of large multidimensional data sets, Multivariate Analysis techniques can help. Hence, in this paper, a methodology using Principal Component Analysis and Multi-Dimensional Scaling is proposed and illustrated by means of two case studies. The first case study evaluates the operation of several wastewater treatment plants. The second case study deals with the environmental evaluation of the cultivation, processing and consumption of mussels. In both case studies, the redundancy present in the data allowed a dimensionality reduction from seven and ten to two dimensions, with a small loss of information. Plotting the environmental impact data in these two dimensions can help visualize, interpret and communicate them.

Lifetime of household appliances: empirical evidence of users behaviour

The household appliance industry is one of the most important sectors from both the economic and environmental point of view. A greater understanding of the way in which consumers of these items behave would help to better plan the recycling needs as a function of previous purchase figures. This paper presents the findings of a field survey of Spanish consumer habits with respect to different common household appliances as regards replacement time and the reasons for replacing these appliances. The methodology used is based on survival analysis; specifically, a competing risks model. A Cox proportional hazards model is also used for the sake of comparison. Our results show that as the number of people and/or persons under 18 years in the household increases, the lifetimes of some types of appliance decrease significantly. Competing risk model shows that the probability of replacing the refrigerator due to malfunction and technological obsolescence increases with the increase of family members with a higher education. We also provide the cumulative incidence function for different appliances, which can be used to forecast future demands and electrical and electronic waste generation.

Dimensionality Reduction and Visualization of the Environmental Impacts of Domestic Appliances

There is an increasing worldwide concern about the problem of dealing with the waste electrical and electronic equipment (WEEE), given the high volume of appliances that are disposed of every day. In this article, an environmental evaluation of WEEE is performed that combines life cycle assessment (LCA) methodology and multivariate statistical techniques. Because LCA handles a large number of data in its different phases, when one is trying to uncover the structure of large multidimensional data sets, multivariate statistical techniques can provide useful information. In particular, principal?component analysis and multidimensional scaling are two important dimension?reducing tools that have been shown to be of help in understanding this type of complex multivariate data set. In this article, we use a variable selection method that reduces the number of categories for which the environmental impacts have to be computed; this step is especially useful when the number of impact categories or the number of products or processes to benchmark increases. We provide a detailed illustration showing how we have used the proposed approach to analyze and interpret the environmental impacts of different domestic appliances.